Dimensional lifting through generalized Gram-Schmidt process
Hans Havlicek, Karl Svozil
TL;DR
This paper introduces a novel orthogonalization technique called dimensional lifting via a generalized Gram-Schmidt process, which elevates vector ensembles to higher dimensions and may aid quantum decision and computing tasks.
Contribution
It presents a new method for orthogonalizing vectors by lifting them to higher dimensions, expanding the tools available for quantum information processing.
Findings
Potential application in quantum decision problems
Enhanced orthogonalization method for vector ensembles
Foundation for future quantum computing algorithms
Abstract
A new way of orthogonalizing ensembles of vectors by "lifting" them to higher dimensions is introduced. This method can potentially be utilized for solving quantum decision and computing problems.
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography